Flight Data Acquisition Methodology for Validation of Passive Ranging Algorithms for Obstacle Avoidance

The automation of rotorcraft low altitude flight depends upon the ability to detect, locate, and navigate around obstacles lying in the rotorcraft’s intended flight path. Computer vision techniques provide a passive method of obstacle detection and range estimation for obstacle avoidance. Several algorithms based on computer vision methods have been developed for this purpose using laboratory data; however, further development and validation of candidate algorithms requires data collected during rotorcraft flight. A database containing low altitude imagery augmented with the rotorcraft and sensor parameters required for passive range estimation is not readily available. This paper will focus on the methodology used to develop such a database from flight test data including imagery, rotorcraft and sensor parameters, and ground truth range measurements. As a part of the data preparation, a new technique for obtaining the sensor calibration parameters is described. The database will enable further development of computer vision based obstacle detection and passive range estimation algorithms as well as provide a benchmark for verification of range estimates against ground truth measurements.